1. Field of the Invention
The present invention relates to an error control method for a digital channel equalizer, and more particularly, to an error control method for a channel equalizer which is capable of improving complexity and error update speed by decreasing the number of gates of a Decision-Directed (DD) error size calculation unit of a combined G-pseudo channel equalizer among digital channel equalizers.
2. Description of the Background Art
Generally, a channel equalizer is an apparatus for decreasing bit detection error by compensating for a restricted bandwidth of a plurality of filters used in a sending/receiving end and a distortion generated while a signal passes through multiple paths of a transmission channel, when a digital transmission system such as a HDTV sends/receives a signal.
If the signal transmitted from the sending end is distorted, contains noise, and has a higher signal level, the error generation rate is increased. Thus, the receiving end utilizes a channel equalizer in order to accurately restore a transmitted signal by compensating for the distortion of a received signal.
The operation of the channel equalizer is divided into an acquisition step of acquiring a signal close to the original signal by reducing error until a distorted, received signal is compensated to be close to the original signal, and a tracking step of configuring the signal whose error is reduced until it becomes close to the original signal so that it meets changes in channel well. Even after the received signal is compensated for, if the signal sent from the sending end is seriously distorted, there occurs a problem that the equalizer diverges. This problem can be overcome by inserting a predetermined training sequence signal into the signal transmitted from the sending end to the receiving end and transmitting the same.
When the training sequence signal is inserted into the transmission signal, the bandwidth of a signal to be transmitted is reduced since the training sequence signal is a signal for correcting an error, and the complexity of the sending end system is increased since an apparatus for generating the training sequence must be added to the sending end system.
Therefore, a blind channel equalizer such as a combined G-pseudo channel equalizer which has an excellent convergence characteristic even if the training sequence signal is not inserted, has been researched and developed.
The combined G-pseudo channel equalizer is an equalizer combining an equalizer utilizing a DD algorithm and an equalizer utilizing a Sato algorithm, each having a DD slicer and a Sato slicer. In the case that a signal received by the G-pseudo channel equalizer is updated by a DD error only, the equalizer is easy to diverge. Thus, convergence is performed by using both DD error and Sato error. In addition, in the case that an error of a signal received by using a Sato error only is updated, there remains a lot of residual errors even after the final convergence. Thus, errors can be reduced by performing convergence using a DD error at the point of time where the convergence is performed to a certain extent.
In the case that a transmission signal to which the training sequence signal is not inserted is inputted, the DD error is an error detected by estimating an approximate value of the original signal from the above input signal, whereas the Sato error is an error detected from the original signal by the mean power of the inputted signal.
FIG. 1 is a block diagram of a combined G-pseudo channel equalizer according to the conventional art, which includes an equalizer filter 10 for correcting an error of received data; a DD(Decision-Directed) slicer for generating a DD error upon receipt of a correction signal outputted from the equalizer filter 10; a DD error size calculation unit 40 for calculating the size of the outputted DD error; a Sato slicer unit 50 for calculating the Sato error upon receipt of the correction signal outputted from the equalizer filter 10; multipliers 30, 60, 70; and an adder 80.
The operation of the thusly constructed combined G-pseudo channel equalizer will be described with reference to FIGS. 1 and 2.
If the signal sent from the sending end is inputted to the channel equalizer via a channel without the training sequence signal, the channel equalizer obtains the optimum value of an inverse response of the channel, this optimum value generating the original signal transmitted from the sending end by multiplying the original signal and the response value of the channel at the output end of the channel equalizer.
The mathematical formula for obtaining the above-described transmitted original signal will be expressed as follows.a·s·s−1=a  (1)
a is the original signal.
s is the response value of the channel.
s−1 is the optimum value of the inverse response of the channel.
If the signal a is inputted to the equalizer filter 10, the optimum value of the inverse response (s−1) of the channel is outputted by correcting an error of the received signal by the equalizer filter 10. The outputted signal is obtained by correcting an error by the DD slicer unit 20 and the Sato slicer unit 50.
In the DD slicer unit 20, a DD silcer 21 performs calculation on the inputted signal to output the most approximate value of the original signal, and an abstractor 22 abstracts the value outputted from the equalizer filter 10 from the outputted approximate value to thus generates a DD error. The generated DD error is multiplied by a scale constant k1 by the multiplier 30 to be automatically converted into the Sato error mode.
In the Sato slicer unit 50, a Sato slice 51 performs calculation on the inputted signal to output the normal value of the inputted value, and an abstractor 52 abstracts the value outputted from the equalizer filter 10 from the calculated normal value to thus generate an Sato error. The generated Sato error is multiplied by a scale constant k2 by the multiplier 60 to be automatically converted into the DD error mode.
Even if the point of time where the Sato error mode and the DD error mode are converted is not set, the generated DD error and the generated Sato error are automatically converted into the Sato error mode and the DD error mode, respectively.
FIG. 2 is a graph comparing the characteristics of a general Sato error and the characteristics of a general DD error. While the DD error has a white value, i.e., a uniform value, the inverse response of the channel obtained from the combined G-pseudo channel equalizer, i.e., a G-pseudo error, is reduced by means of a Sato error. However, at point t1 of time in a certain section, the Sato error becomes uniform. Since then, the G-pseudo error is reduced by means of the DD error.
The Sato error has a considerable error value even after it has converged on the optimum point, i.e., until the equalizer outputs a signal close to the optimum value of the inverse response s−1 of the channel. Thus, if the DD error and the Sato error are added, the G-pseudo error has an error value as much as the Sato error even though the DD error has an error value of almost 0. This is the limitation on the blind method.
For this reason, if the Sato error multiplied by the scale constant is multiplied by the absolute value of the DD error calculated in the DD error size calculation unit 40, the DD error has a white value, i.e., a uniform value in the first section where the optimum value of the inverse response s−1 is searched for, thereby not affecting the G-pseudo error. At this time, the G-pseudo error is reduced by the Sato error. However, as the Sato error becomes uniform in the section t1, i.e., it converges on 0 in the section t1, the G-pseudo error value is reduced by the DD error value. Thus, the optimum value of the inverse response of the channel can be searched for by means of the DD error only.
The above described coefficient updating equation and filter output equation can be expressed as follows.
                              C                      k            +            1                          =                              C            k                    +                      μ            ⁢                                                  ⁢                          D              k              *                        ⁢                          e              k              G                                                          (        2        )                                          Y          ⁡                      (            n            )                          =                  ∑                                    D              T                        ⁢            C                                              (        3        )                                          e          k          G                =                                            k              1                        ⁢                          e              k                                +                                    k              2                        ⁢                                                        e                k                                                    ⁢                          e              k              S                                                          (        4        )                                                                e            k                                    =                                            e              1              2                        +                          e              Q              2                                                          (        5        )                            Ck+1 is a coefficient of a filter tab of an equalizer of the next time.        Ck is a coefficient of a filter tab of an equalizer of the current time. is the size of a step.        Dk is a data stored in the filter tab of the current time.        ekG is a G-pseudo error of the current time.        ekS is a Sato error of the current time.        ek is a DD error of the current time.        k1 and k2 are scale constants.        e1 is a real error.        eQ is an imaginary error.        
The value obtained by multiplying the Sato error by a scale constant k2 is multiplied by the value |ek| calculated in the DD error calculation unit 40, and then the resultant value |ek|ekS is added to the value obtained by multiplying the DD error by the scale constant k1, for thereby obtaining the optimum value s−1 of the G-pseudo equalizer.
The optimum value s−1 obtained by the G-pseudo channel equalizer performs convergence well in most channel environments. However, since the value |ek| calculated in the DD error calculation unit 40 is the square root of the sum of a real error square and an imaginary square, i.e., √{square root over (e12+eQ2)}, the complexity of the DD error calculation unit 40 is increased. In the case that the DD error calculation unit 40 is implemented, a large number of gates are required, for thereby increasing the size thereof and the complexity. In addition, it takes much time to obtain the square root, which degrades the performance of a receiver.